• Title/Summary/Keyword: 교통 데이터맵

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클라우드 기반 VTS 서비스 운용을 위한 중장기 로드맵에 관한 연구

  • 김대원;박영수;이명기;김소라;교칸 참르율트;송재욱
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.06a
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    • pp.260-261
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    • 2022
  • 해양경찰청에서는 2021년부터 기존에 구축되어 운영 중인 선박교통관제(VTS) 시스템에 클라우드 신기술을 적용하기 위한 기술개발 연구에 착수하였으며, 이를 통하여 데이터의 효과적인 관리, 관제 정보 접근성 개선 등의 기술적 패러다임의 전환을 추구하고 있다. 해당 과제의 성공적인 수행을 위해서는 관제 데이터 운용에서부터 관제운영 시스템, 인력 구성, 교육·훈련 및 제 규정 등 선박교통관제 전 분야에 걸쳐 새로운 정의가 필요하다. 이를 위해 본 연구에서는 클라우드 VTS 서비스 제공을 위한 중·장기 로드맵 작성의 첫 단계로써 관련 문헌 연구를 통하여 핵심 키워드를 도출해 보고자 한다.

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Developing RDF Meta data Graph for Transportation Open Data Platform (교통데이터 유통을 위한 RDF 메타 데이터 그래프 구축방안)

  • Park, Eun Mi;Kang, Jung Hyun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.6
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    • pp.110-116
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    • 2021
  • W3C enacted RDF(Resource Description Framework based DCAT meta data standard, which is world-widely accepted so far. To guarantee the inter-operability and integrity of data from various sources and even from various countries, it is considered that transportation meta data should also follow the DCAT standard. But still, to represent the transportation domain-specific features, it is necessary to define new properties and vocabularies in addition to the DCAT standard. This research identified the additional properties and vocabularies for transportation metadata, considering uniqueness of transportation data. The revised RDF schema and RDF graph proposed in this research should be able to lead the transportation open data platform revitalization.

A Trip Mobility Analysis using Big Data (빅데이터 기반의 모빌리티 분석)

  • Cho, Bumchul;Kim, Juyoung;Kim, Dong-ho
    • The Journal of Bigdata
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    • v.5 no.2
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    • pp.85-95
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    • 2020
  • In this study, a mobility analysis method is suggested to estimate an O/D trip demand estimation using Mobile Phone Signaling Data. Using mobile data based on mobile base station location information, a trip chain database was established for each person and daily traffic patterns were analyzed. In addition, a new algorithm was developed to determine the traffic characteristics of their mobilities. To correct the ping pong handover problem of communication data itself, the methodology was developed and the criteria for stay time was set to distinguish pass by between stay within the influence area. The big-data based method is applied to analyze the mobility pattern in inter-regional trip and intra-regional trip in both of an urban area and a rural city. When comparing it with the results with traditional methods, it seems that the new methodology has a possibility to be applied to the national survey projects in the future.

An Estimation Methodology of Empirical Flow-density Diagram Using Vision Sensor-based Probe Vehicles' Time Headway Data (개별 차량의 비전 센서 기반 차두 시간 데이터를 활용한 경험적 교통류 모형 추정 방법론)

  • Kim, Dong Min;Shim, Jisup
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.2
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    • pp.17-32
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    • 2022
  • This study explored an approach to estimate a flow-density diagram(FD) on a link in highway traffic environment by utilizing probe vehicles' time headway records. To study empirical flow-density diagram(EFD), the probe vehicles with vision sensors were recruited for collecting driving records for nine months and the vision sensor data pre-processing and GIS-based map matching were implemented. Then, we examined the new EFDs to evaluate validity with reference diagrams which is derived from loop detection traffic data. The probability distributions of time headway and distance headway as well as standard deviation of flow and density were utilized in examination. As a result, it turned out that the main factors for estimation errors are the limited number of probe vehicles and bias of flow status. We finally suggest a method to improve the accuracy of EFD model.

Implementation of the OLAP-based Subway Passenger Transit Pattern Analysis System (OLAP을 활용한 지하철 인구이동 맵 생성에 관한 연구)

  • Cho, Jae-Hee;Seo, Il-Jung
    • Information Systems Review
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    • v.7 no.1
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    • pp.65-80
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    • 2005
  • The Seoul Metropolitan Subway Corporation (SMS) and the Seoul Metropolitan Rapid Transit Corporation (SMRT), which manage the city's eight subway lines, are intending to overcome their operational inefficiencies. The two investigators of the paper realize with emphasis that it is essential for the two subway authorities to analyze subway transit data prior to put policies and plans into practice. In this paper, the investigators propose a new, and an intuitive, way of analyzing subway passenger transit patterns. To achieve this goal, they have implemented a data mart by blending the "Pass Card" log data into the multidimensional model. The subway passenger's transit patterns and the practical implications of this system are also investigated.

Research on the Analysis of Maritime Traffic Pattern using Centroid Method (중심점 기법을 이용한 통항패턴 분석에 관한 연구)

  • Kim, Hye-Jin;Oh, Jae-Yong
    • Journal of Navigation and Port Research
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    • v.42 no.6
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    • pp.453-458
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    • 2018
  • The analysis of maritime traffic refers to the processes that are used to analyze the environmental characteristics of the target area and, based on this analysis, predict the traffic pattern of the vessels. In recent years, maritime traffic analysis has become significant with increase maritime traffic volume and expansion of VTS coverage area. In addition, maritime traffic analysis is also applicable in the safety assessment of port facilities and the VTS (Vessel Traffic Service). In this paper, we propose a method to analyze the vessels' traffic pattern by using the heat map and the centroid method. This method is efficient for the analysis of the vessel trajectory data where spatial characteristics change with time. In the experiments, the traffic density and centroid by time have were analyzed. Trajectory data collected at Mokpo harbor was adopted. Finally, we reviewed the experimental results to verify the feasibility of the proposed method as a maritime traffic analysis method.

Trends on High-Precision Digital Map for Autonomous Driving Services (클라우드 연계 자율주행 맵 시스템 기술동향)

  • Choi, J.D.;Min, K.W.;Sung, K.B.;Han, S.J.;Lee, D.J.;Park, S.H.;Kang, J.G.;Jo, Y.W.
    • Electronics and Telecommunications Trends
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    • v.32 no.4
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    • pp.40-47
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    • 2017
  • 자율주행 맵은 도로의 주행환경 정보(차로, 도로 마크, 신호등의 위치 등)와 시간에 따라 변화하는 동적 주행환경 정보(장애물 출현, 일시적인 통행제한, 긴급한 도로 복구, 교차로 교통혼잡 등)로 구성된다. 자율주행 맵 생성 및 갱신 기술은 차로 구분선이나, 도로 교통과 관련된 실시간 갱신 주기 측면에서 더욱 세밀하고, 정확한 위치 정보가 요구되며, 또한, 최신성을 유지하는 기능을 가진다. 이러한 고정밀 지도의 세밀함과 정확성, 최신성은 자율주행 서비스를 위해 요구되는 필수적인 요소이다. 클라우드와 연계하여 생성되는 자율주행 맵은 차량 운행 시 수집되는 정보를 클라우드에 축적하여 가공함으로써, 시간과 인력 투입을 통해 데이터를 취득하고 지도를 구축하는 면에서 작업 품을 효과적으로 개선하는 데 도움이 된다. 유지와 보수 측면에서는 정기적으로 또는 신속하게 갱신하여 최신의 정보를 유지하는 장점이 있다. 본고에서는 자율주행 맵을 생성하고 갱신하는 클라우드 연계 플랫폼과 연구 결과 일부를 소개한다.

Travel Time Prediction Algorithm for Trajectory data by using Rule-Based Classification on MapReduce (맵리듀스 환경에서 규칙 기반 분류화를 이용한 궤적 데이터 주행 시간 예측 알고리즘)

  • Kim, JaeWon;Lee, HyunJo;Chang, JaeWoo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2014.11a
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    • pp.798-801
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    • 2014
  • 여행 정보 시스템(ATIS), 교통 관리 시스템 (ITS) 등 궤적 기반 서비스에서, 서비스 품질을 향상시키기 위해서는 주어진 궤적 질의에 대한 정확한 주행시간을 예측하는 것이 필수적이다. 이를 위한 대표적인 공간 데이터 분석 기법으로는 데이터 분류에서 높은 정확도를 보장하는 규칙 기반 분류화 기법이 존재한다. 그러나 기존 규칙 기반 분류화 기법은 단일 컴퓨터 환경만을 고려하기 때문에, 대용량 공간 데이터 처리에 적합하지 않은 문제점이 존재한다. 이를 해결하기 위해, 본 연구에서는 맵리듀스 환경에서 규칙 기반 분류화를 이용한 궤적 데이터 주행 시간 예측 알고리즘을 개발하고자 한다. 제안하는 알고리즘은 첫째, 맵리듀스를 이용하여 대용량 공간 데이터를 병렬적으로 분석함으로써, 활용도 높은 궤적 데이터 규칙을 생성한다. 이를 통해 대용량 공간 데이터 기반의 규칙 생성 시간을 감소시킨다. 둘째, 그리드 구조 기반의 지도 데이터 분할을 통해, 사용자 질의처리 시 탐색 성능을 향상시킨다. 즉, 주행 시간 예측을 위한 규칙 그룹을 탐색 시 질의를 포함하는 그리드 셀만을 탐색하기 때문에, 질의처리 성능이 향상된다. 마지막으로 맵리듀스 구조에 적합한 질의처리 알고리즘을 설계하여, 효율적인 병렬 질의처리를 지원한다. 이를 위해 맵 함수에서는 선정된 그리드 셀에 대해, 질의에 포함된 도로 구간에서의 주행 시간을 병렬적으로 측정한다. 아울러 리듀스 함수에서는 출발 시간 및 구간별 주행 시간을 바탕으로 맵 함수의 결과를 병합함으로써, 최종 결과를 생성한다. 이를 통해 공간 빅데이터 분석을 통한 주행 시간 예측 기법의 처리 시간 및 결과 정확도를 향상시킨다.

Analysis of overlap ratio for registration accuracy improvement of 3D point cloud data at construction sites (건설현장 3차원 점군 데이터 정합 정확성 향상을 위한 중첩비율 분석)

  • Park, Su-Yeul;Kim, Seok
    • Journal of KIBIM
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    • v.11 no.4
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    • pp.1-9
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    • 2021
  • Comparing to general scanning data, the 3D digital map for large construction sites and complex buildings consists of millions of points. The large construction site needs to be scanned multiple times by drone photogrammetry or terrestrial laser scanner (TLS) survey. The scanned point cloud data are required to be registrated with high resolution and high point density. Unlike the registration of 2D data, the matrix of translation and rotation are used for registration of 3D point cloud data. Archiving high accuracy with 3D point cloud data is not easy due to 3D Cartesian coordinate system. Therefore, in this study, iterative closest point (ICP) registration method for improve accuracy of 3D digital map was employed by different overlap ratio on 3D digital maps. This study conducted the accuracy test using different overlap ratios of two digital maps from 10% to 100%. The results of the accuracy test presented the optimal overlap ratios for an ICP registration method on digital maps.

Performance Evaluation of Denoising Algorithms for the 3D Construction Digital Map (건설현장 적용을 위한 디지털맵 노이즈 제거 알고리즘 성능평가)

  • Park, Su-Yeul;Kim, Seok
    • Journal of KIBIM
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    • v.10 no.4
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    • pp.32-39
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    • 2020
  • In recent years, the construction industry is getting bigger and more complex, so it is becoming difficult to acquire point cloud data for construction equipments and workers. Point cloud data is measured using a drone and MMS(Mobile Mapping System), and the collected point cloud data is used to create a 3D digital map. In particular, the construction site is located at outdoors and there are many irregular terrains, making it difficult to collect point cloud data. For these reasons, adopting a noise reduction algorithm suitable for the characteristics of the construction industry can affect the improvement of the analysis accuracy of digital maps. This is related to various environments and variables of the construction site. Therefore, this study reviewed and analyzed the existing research and techniques on the noise reduction algorithm. And based on the results of literature review, performance evaluation of major noise reduction algorithms was conducted for digital maps of construction sites. As a result of the performance evaluation in this study, the voxel grid algorithm showed relatively less execution time than the statistical outlier removal algorithm. In addition, analysis results in slope, space, and earth walls of the construction site digital map showed that the voxel grid algorithm was relatively superior to the statistical outlier removal algorithm and that the noise removal performance of voxel grid algorithm was superior and the object preservation ability was also superior. In the future, based on the results reviewed through the performance evaluation of the noise reduction algorithm of this study, we will develop a noise reduction algorithm for 3D point cloud data that reflects the characteristics of the construction site.